The uncertain future of dairy data governance

Farmers advised to ask questions when buying new technology

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With high-tech robot barns leading the way, and many dairy farmers with older-style milking systems adding sensors, the collection of real-time data about cow care has exploded in the past few years.

The rapid increase of sensors and in-barn artificial intelligence (AI) has given rise to new issues previously not considered.

Why it matters: Dairy farmers are being told by equipment suppliers about the value of new information-gathering technology, but they need to have confidence that any purchase makes long-term financial sense.

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A big question, said Lactanet’s national director for business development Richard Cantin, is “data governance.”

Lactanet was formed when CanWest DHI, Valacta and the Canadian Dairy Network came together recently to form a new organization.

Cantin said the entire dairy industry needs to begin tackling the issue of who owns the data gathered on farms.

It’s often generated by equipment sold to farmers by private companies, he told Farmtario in a recent interview, and those companies typically argue the knowledge behind that data generation is proprietary, and therefore the data is proprietary.

Older technologies such as milk meters or sending milk samples for testing at a laboratory are a world away from the real-time sensors that send information to farmers’ smartphones today.

“Often, these new technologies have algorithms behind them,” Cantin said. “So companies view the technology they have as a competitive advantage over other companies in the market. And they want to be able to retain control of how that data is used.”

“And often, farmers say, ‘no, this should be my data because it was generated on my farm’.”

According to Lactanet data scientist René Lacroix, those farmers aren’t alone. Lobby groups have formed in the United States and European Union but not yet in Canada, he told Farmtario, advocating for “the data that are collected on farms (to) be housed in central databases that are under the control of producers.”

“We’re definitely in a big grey area that will sort itself out over time,” Cantin said. “And dairy is definitely not the only industry that’s facing that. On the crop side, it’s maybe even more of a concern, if only because the technology seems to be concentrated in the hands of even fewer companies.”

It’s difficult, he added, to figure out who should take leadership roles in the creation of a regulatory regime for on-farm-generated data governance. Do farmers want the government to decide on its own or should there be consultations? If there is to be consultations, whose perspectives should be given more weight? Private companies? Or farmers? Lactanet, being a farmer-controlled organization, wants to play a role, and Cantin believed it would be in the best interests of farmers if it can play a leadership role.

Dairy farmers need to recognize that they have clout, as the purchasers of the technology. They should make it known they want access to and the freedom to use the data from their farm as they choose and Cantin said anyone buying new technology to have some sort of agreement drawn up ensuring that happens.

Similarly, farmers should recognize they have clout in directing what types of data are gathered on their farm. There’s no sense trying to detect a disease when your farm, historically, has zero incidence level, just because an equipment supplier reports that other farmers in the region find it useful.

Lacroix said that as the sector continues down this path of AI use, a key need is to build capacity to create what he called on-farm digital audits.

“With all these devices producing all this information, we can easily be overwhelmed,” he said. Time spent dealing with the data becomes a valuable resource.

Lactanet has begun looking into how to create a new digital “dashboard” to guide decision-making. “Ideally, we should have algorithms,” Lacroix explained, that assess and coordinate the different data for each producer, and can “point out to the producer that you have a problem here, or there,” as well as propose solutions. “Ideally, because that’s what AI is supposed to do — the magic of AI. But how we get there is another question.”

The “digital audits,” which already exist in other industrial or business applications, would see a third-party consultant come in and assess all the processes on the farm, and how the data flows from one place to another.

Digital audits and digital dashboards are in the future, though. For now, Cantin admitted, farmers are “often left on their own to bring it together, which can be a challenge.”

Still lots to learn

“Often, the information is a little bit ‘apples and oranges’,” Cantin said, referring to the possible scenario in which data is generated on the same farm using different technologies supplied by different manufacturers, and different units of measurement. “So, when you go to integrate it, you don’t always know how reliable the results are that you get.”

Even two robots supplied by the same company and installed at the same time on the same farm, Lacroix said, could potentially provide different quality results for a sample of milk, if they happened to be calibrated by a different person or in a different manner.

In addition, equipment suppliers face challenges in ensuring their service people and sales staff know how to advise their customers. And organizations like Lactanet also have a lot to learn.

To that end, about a year ago, the board of Valacta created the Comité Stratégique sur le Virage Numérique (Strategy Committee for the Digitalization of Dairy), and that committee has been continued through the transition to Lactanet. Thirteen organizations are involved, and their early work was to contract a consultant with a mandate to look at data governance, data access, and adding value to the data being gathered. According to Lacroix, that consultants’ report should be finished by the end of December or early January.

For now, he advised farmers to be cautious. Along with demanding an agreement around access to and ownership of data, he says farmers should request “validation” of the claims made by equipment suppliers. “For example, if (the supplier salesperson) says ‘this technology is going to increase your herd’s conception rate,’ ask them to show you the studies showing that’s the case.”

“There are a lot of claims being made around these technologies and, honestly, there’s not always data to support those claims.”

About the author

Contributor

Stew Slater operates a small dairy farm on 150 acres near St. Marys, Ont., and has been writing about rural and agricultural issues since 1999.

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